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. 2020;4(4):295-299.
doi: 10.1080/24748706.2020.1782549. Epub 2020 Jul 9.

Can Clinical Predictive Models Identify Patients Who Should Not Receive TAVR? A Systematic Review

Benjamin S Wessler  1   2 , Andrew R Weintraub  1 , James E Udelson  1 , David M Kent  2
Affiliations

Can Clinical Predictive Models Identify Patients Who Should Not Receive TAVR? A Systematic Review

Benjamin S Wessler et al. Struct Heart. 2020.

Abstract

Background: One third of high- and prohibitive-risk TAVR patients remain severely symptomatic or die 1 year after treatment. There is interest in identifying individuals for whom this procedure is futile and should not be offered.

Methods: We performed a systematic review of the highest reported stratum of risk in TAVR clinical predictive models (CPMs). We explore whether currently available predictive models can identify patients for whom TAVR is futile, based on a quantitative futility definition and the observed and predicted outcomes for patients in the highest stratum of risk.

Results: 17 TAVR CPMs representing 69,191 treated patients were published from 2013 to 2018. When reported, the median number of patients in the highest stratum of risk was 569 (range 1 to 1759). Observed mortality for this risk stratum ranged from 9% at 30 days to 59% at 1 year after TAVR. Statistical confidence in these observed event rates was low. The highest predicted event rates ranged from 11.0% for in-hospital mortality to 75.1% for the composite of mortality or high symptom burden 1 year after TAVR.

Conclusion: No high-risk TAVR group in currently available TAVR CPMs had an appropriate event rate and adequate statistical power to meet a quantitative definition of futility.

Keywords: Clinical Cardiology; Interventional Cardiology; Non-invasive and minimally invasive Cardiology.

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Conflict of interest statement

Disclosure statement: The authors have no conflicts of interest to report.

Figures

Figure 1.
Figure 1.
Each of these 13 columns represents data from an individual TAVR CPM. The predicted and observed event rates for patients identified as the highest risk are depicted on the y-axis. Colors represent different time horizons, which are shown on the x-axis (In-hospital, 30 days, 6 months and 1 year). o represent observed event rates, error bars represent 95% CI surrounding the observed event rates in the highest risk strata. + represent observed rates where no CI can be calculated. x represent predicted mortality rates. ∆ represents predicted composite of mortality or high symptom burden. Not every column has complete information on observed and predicted data or confidence intervals, as most CPMs report incomplete data.
See this image and copyright information in PMC

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